Zobrazeno 1 - 10
of 108 503
pro vyhledávání: '"A, Coates"'
Autor:
Zhou, Jiaming, Ghaddar, Abbas, Zhang, Ge, Ma, Liheng, Hu, Yaochen, Pal, Soumyasundar, Coates, Mark, Wang, Bin, Zhang, Yingxue, Hao, Jianye
Despite recent advances in training and prompting strategies for Large Language Models (LLMs), these models continue to face challenges with complex logical reasoning tasks that involve long reasoning chains. In this work, we explore the potential an
Externí odkaz:
http://arxiv.org/abs/2409.12437
Autor:
Verbas, Omer, Cokyasar, Taner, Joyce-Johnson, Seamus, Wainwright, Scott, Coates, Maeve, Rousseau, Aymeric, Aloisi, Jim, Stewart, Anson, Auld, Joshua
Transit is essential for urban transportation and achieving net-zero targets. In urban areas like the Chicago Metropolitan Region, transit enhances mobility and connects people, fostering a dynamic economy. To quantify the mobility and selected econo
Externí odkaz:
http://arxiv.org/abs/2409.04568
Autor:
Pynn-Coates, Nigel
This paper concerns pairs of models of the theory of the differential field of logarithmic-exponential transseries that are tame as a pair of real closed fields. That is, the smaller model is bounded inside the larger model and there exists a standar
Externí odkaz:
http://arxiv.org/abs/2408.07033
Inspired by transformation optics and photonic crystals, this paper presents a computational investigation into the interaction between water surface waves and array waveguides of cylinders with multiple previously unexplored lattice geometries, incl
Externí odkaz:
http://arxiv.org/abs/2407.17141
In this article we show that a large class of infinite measure preserving dynamical systems that do not admit physical measures nevertheless exhibit strong statistical properties. In particular, we give sufficient conditions for existence of a distin
Externí odkaz:
http://arxiv.org/abs/2407.07286
Autor:
Regol, Florence, Chataoui, Joud, Charpentier, Bertrand, Coates, Mark, Piantanida, Pablo, Gunnemann, Stephan
Machine learning models can solve complex tasks but often require significant computational resources during inference. This has led to the development of various post-training computation reduction methods that tackle this issue in different ways, s
Externí odkaz:
http://arxiv.org/abs/2406.14404
Autor:
Guéroult, Quentin, Bulled, Jonathan, Patteson, Henry, Coates, Chloe, Smith, Ronald, Playford, Helen, Keen, David, Goodwin, Andrew
The transition-metal dicyanides M(CN)$_2$ (M = Zn, Cd) are amongst the most important negative thermal expansion (NTE) materials known, favoured for the magnitude, isotropy, and thermal persistence of the NTE behaviour they show. The conventional pic
Externí odkaz:
http://arxiv.org/abs/2406.11381
Autor:
Rumiantsev, Pavel, Coates, Mark
In terms of accuracy, Graph Neural Networks (GNNs) are the best architectural choice for the node classification task. Their drawback in real-world deployment is the latency that emerges from the neighbourhood processing operation. One solution to th
Externí odkaz:
http://arxiv.org/abs/2406.11919
The van der Heijde modification of the Sharp (SvdH) score is a widely used radiographic scoring method to quantify damage in Rheumatoid Arthritis (RA) in clinical trials. However, its complexity with a necessity to score each individual joint, and th
Externí odkaz:
http://arxiv.org/abs/2406.09980
Online deep learning solves the problem of learning from streams of data, reconciling two opposing objectives: learn fast and learn deep. Existing work focuses almost exclusively on exploring pure deep learning solutions, which are much better suited
Externí odkaz:
http://arxiv.org/abs/2405.18281